The present invention generally relates to virtual machine acceleration in virtual environments and, more particularly, applying a non-volatile memory-based cache architecture in a hypervisor environment.
Data center virtualization technologies are now well adopted into information technology infrastructures. As more and more applications are deployed in a virtualized infrastructure, there is a growing need for performance acceleration, virtualization services and business continuity in various levels.
A virtual server is a type of virtual machine, which as used herein refers to software that executes programs like a physical machine. Virtual servers are logical entities that run as software in a server virtualization infrastructure, referred to as a “hypervisor” or a virtual machine manager. A hypervisor provides storage device emulation, referred to as “virtual disks”, to virtual servers. Hypervisors implement virtual disks using back-end technologies, such as files on a dedicated file system, or raw mapping to physical devices.
Whereas physical servers run on hardware, virtual servers run their operating systems within an emulation layer that is provided by a hypervisor. Virtual servers may be implemented in software to perform the same tasks as physical servers. Such tasks include, for example, running server applications, such as database applications, customer relation management (CRM) applications, email servers, and the like. Most applications that run on physical servers are portable to run on virtual servers. Within the context of virtualization, one distinction should be mentioned for clarification purposes, which is, the distinction between virtual desktops and virtual servers: virtual desktops run client side applications and service individual users, whereas virtual servers run applications that service multiple and potentially large numbers of clients.
The goal of virtual servers is to provide high performance, high availability, data integrity and data continuity. Virtual servers are dynamic in the sense that they may be moved from one host server computer system to another. This also entails that on a single host server computer system the number of virtual servers may vary over time since virtual machines can be added and removed from the host server computer system at any time.
As computing resources, such as CPU and memory, are provided to the virtual server by the hypervisor, the main bottleneck for the virtual server's operation resides in the storage path. Hard disk drives (HDDs) in particular, being electro-mechanical devices with all their known drawbacks, are hampered by low performance, especially in random pattern workload situations due to their rotational and seek latencies.
A solid-state drive (SSD) is a drive that uses solid-state technology to store its information and provide access to the stored information via a storage interface. The most common SSDs use NAND flash memory arrays to store the data and a controller serving as the interface between the host server computer system and the NAND flash memory array. Such a controller can use internal DRAM or SRAM memory, battery backup, and other elements.
In contrast to a magnetic hard disk drive, a non-volatile memory-based storage device (SSD or raw flash, for example, direct memory mapped rather than a block device behind a SATA interface) is an electronic device and does not contain any moving parts. As a result, seek and rotational latencies inherent in hard disk drives are almost completely eliminated in non-volatile memory-based storage devices resulting in read and write requests being serviced in an immediate operation. Thus, a flash-based device has greatly improved performance over hard disk drives, especially in an environment defined by mostly small read and write operations with random patterns.
Due to the much higher cost of non-volatile memory-based storage and limited data retention relative to magnetic hard disks, back end storage mainly uses magnetic hard disks as the primary storage tier. However, non-volatile memory-based storage acceleration is achieved in the storage level, for example, by means of caching or tiering mechanisms.
Conventional virtualization acceleration systems for disk I/O are often implemented at the physical disk level, which means they are not specifically designed to handle the demands by the virtualization paradigm, for the simple reason that they are not implemented at the hypervisor level. Consequently, these systems are not fully virtualization aware. More specifically, acceleration implemented outside the hypervisor environment suffers from inefficiency, lack of coordination between the services, multiple services to manage and recover, and lack of synergy. Therefore, it is advantageous to establish a unified environment of acceleration in the hypervisor which is much more efficient, simpler to manage, and dynamically adaptive to the changing virtual machine storage needs and synergy.
Furthermore, commonly, the main storage is located outside the physical server in a storage area network (SAN) or network attached storage (NAS) configuration to allow for multiple accesses by all physical servers and allow migration of the virtual machine. In contrast, non-volatile memory-based storage devices for caching can be placed in the physical server itself, thus providing faster access to the media with lower latency due to the short distance compared to the external storage. The capacity of the cache is limited due to its location on the physical server. Therefore, efficient caching algorithms must make complex decisions on what part of the data to cache and what not to cache. In order to be successful, these advanced algorithms for caching also require the collection of storage usage statistics over time for making an informed decision on what to cache and when to cache it.
A major aspect in virtual environment acceleration compared to a physical environment (i.e., single server) is its heterogeneous nature. Because of the plurality of virtual machines, different workload peak times coincide with different workload patterns and different service levels required. For example, a virtual environment can host a database for transaction processing during the day, and switch to database analysis for the night in addition to virtual desktops that boot together at the start of a shift and so on. As a result, virtual environment caching should support multiple, diverse modes of acceleration, while providing shared and dynamic resources for different applications at different times.
In view of the above, it can be appreciated that there are certain problems, shortcomings or disadvantages associated with the prior art, and that it would be desirable if an improved system and method were available for virtual machine acceleration in virtual environments that implements cache mechanisms on the hypervisor level and implements efficient cache algorithms.